Caching and database scaling in distributed shared-nothing information retrieval systems:
Abstract: "A common class of existing information retrieval system provides access to abstracts. For example Stanford University, through its FOLIO system, provides access to the INSPEC database of abstracts of the literature on physics, computer science, electrical engineering, etc. In this pa...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Stanford, Calif.
1992
|
| Series: | Stanford University / Computer Science Department: Report STAN CS
1456 |
| Subjects: | |
| Summary: | Abstract: "A common class of existing information retrieval system provides access to abstracts. For example Stanford University, through its FOLIO system, provides access to the INSPEC database of abstracts of the literature on physics, computer science, electrical engineering, etc. In this paper this database is studied by using a trace- driven simulation. We focus on physical index design, inverted index caching, and database scaling in a distributed shared-nothing system. All three issues are shown to have a strong effect on response time and throughput. Database scaling is explored in two ways. One way assumes an 'optimal' configuration for a single host and then linearly scales the database by duplicating the host architecture as needed The second way determines the optimal number of hosts given a fixed database size. |
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| 520 | 3 | |a Abstract: "A common class of existing information retrieval system provides access to abstracts. For example Stanford University, through its FOLIO system, provides access to the INSPEC database of abstracts of the literature on physics, computer science, electrical engineering, etc. In this paper this database is studied by using a trace- driven simulation. We focus on physical index design, inverted index caching, and database scaling in a distributed shared-nothing system. All three issues are shown to have a strong effect on response time and throughput. Database scaling is explored in two ways. One way assumes an 'optimal' configuration for a single host and then linearly scales the database by duplicating the host architecture as needed | |
| 520 | 3 | |a The second way determines the optimal number of hosts given a fixed database size. | |
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| indexdate | 2024-07-09T17:28:25Z |
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| language | English |
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| series2 | Stanford University / Computer Science Department: Report STAN CS |
| spelling | Tomasic, Anthony Verfasser aut Caching and database scaling in distributed shared-nothing information retrieval systems by Anthony Tomasic and Hector Garcia-Molina Stanford, Calif. 1992 21 S. txt rdacontent n rdamedia nc rdacarrier Stanford University / Computer Science Department: Report STAN CS 1456 Abstract: "A common class of existing information retrieval system provides access to abstracts. For example Stanford University, through its FOLIO system, provides access to the INSPEC database of abstracts of the literature on physics, computer science, electrical engineering, etc. In this paper this database is studied by using a trace- driven simulation. We focus on physical index design, inverted index caching, and database scaling in a distributed shared-nothing system. All three issues are shown to have a strong effect on response time and throughput. Database scaling is explored in two ways. One way assumes an 'optimal' configuration for a single host and then linearly scales the database by duplicating the host architecture as needed The second way determines the optimal number of hosts given a fixed database size. Cache memory Distributed databases Garcia-Molina, Hector Verfasser aut Computer Science Department: Report STAN CS Stanford University 1456 (DE-604)BV008928280 1456 |
| spellingShingle | Tomasic, Anthony Garcia-Molina, Hector Caching and database scaling in distributed shared-nothing information retrieval systems Cache memory Distributed databases |
| title | Caching and database scaling in distributed shared-nothing information retrieval systems |
| title_auth | Caching and database scaling in distributed shared-nothing information retrieval systems |
| title_exact_search | Caching and database scaling in distributed shared-nothing information retrieval systems |
| title_full | Caching and database scaling in distributed shared-nothing information retrieval systems by Anthony Tomasic and Hector Garcia-Molina |
| title_fullStr | Caching and database scaling in distributed shared-nothing information retrieval systems by Anthony Tomasic and Hector Garcia-Molina |
| title_full_unstemmed | Caching and database scaling in distributed shared-nothing information retrieval systems by Anthony Tomasic and Hector Garcia-Molina |
| title_short | Caching and database scaling in distributed shared-nothing information retrieval systems |
| title_sort | caching and database scaling in distributed shared nothing information retrieval systems |
| topic | Cache memory Distributed databases |
| topic_facet | Cache memory Distributed databases |
| volume_link | (DE-604)BV008928280 |
| work_keys_str_mv | AT tomasicanthony cachinganddatabasescalingindistributedsharednothinginformationretrievalsystems AT garciamolinahector cachinganddatabasescalingindistributedsharednothinginformationretrievalsystems |